Voice labeling error detecting system, voice labeling error detecting method and program

Abstract

A labeling part 3 analyzes the character string data to produce a phoneme label and a prosody label, partition the voice data stored in a voice database 1 into phonemic data, and label the phonemic data, employing the phoneme label and the like. A phoneme segmenting part 4 connects the voice data labeled with the same kind of phonemic data, and a formant extracting part 5 specifies the frequency of formant of each piece of phonemic data. A processing part 6 decides an evaluation value for each phonemic data based on the frequency of formant, and an error detection part 7 detects the phonemic data of which a deviation of the evaluation value within a set of phonemic data reaches a predetermined amount.

Description

[0001]This application claims priority from Japanese Patent Application No.2003-302646 filed Aug. 27, 2003, which is hereby incorporated by reference.BACKGROUND OF THE INVENTION[0002]1. Field of the Invention[0003]The present invention relates to a voice labeling error detecting system, a voice labeling error detecting method and a program.[0004]2. Related Background Art[0005]In recent years, the technique of speech synthesis has been widely employed to synthesize the voice. More specifically, there are a number of scenes of using the voice such as a text reading software, the directory inquiry, stock information, travel guide, shop guide, and traffic information, for example.[0006]The speech synthesis methods are largely classified into a rule base method and a waveform editing method (corpus base method).[0007]The rule base method is a method for producing a voice by making morphological analysis for a text to synthesize a speech, and phonetic processing for the text, based on the...

AI Technical Summary

Benefits of technology

The invention provides a system, method, and program for automatically detecting errors in labeling voice data. The system uses a combination of data acquisition, classification, evaluation value decision, and error detection to detect and correct labeling errors. This helps to create a more accurate and reliable voice labeling system.

Problems solved by technology

However, with the automatic labeling method based on the result of voice recognition, a labeling error is still likely to occur, though various improvements have been made.

Conventionally, the verification of labeling error has been manually made, which causes much labor.

Therefore, even if the labeling was automatically performed, the voice corpus with accurate labeling was not necessarily constructed easily.

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